Journal of Pressure Vessel Technology · 2014 · 22 citations · 14 references
Natural SciencesMaterials ScienceSoil SciencesCorrosion ScienceGeotechnical EngineeringSoil SalinityCorrosion EngineeringCorrosion EvaluationCorrosion KineticsCorrosion MonitoringCorrosion Of SteelsCorrosion TestingChloride ContentCorrosion ModelingCorrosion PredictionCorrosion Prediction ModelsMoisture ContentPipeline CorrosionSoil ResistivityUnderground Steel Corrosion
A simple yet practical model to estimate the time dependence of metal loss (ML) in underground pipelines has been developed considering the in situ soil parameters. These parameters are soil resistivity, pH, moisture content, chloride content, and salinity. The time dependence of the ML was modeled as Pmax = ktn, where t is the time exposure, k is ML constant, and n is the corrosion growth pattern. The results of ML and in situ parameters were analyzed using statistical methods such as data screening, linear correlation analysis, principal component analysis, and multiple linear regressions. The best model revealed that k is principally influenced by ressistivity, and n appears to be correlated with chloride content. Model optimization was carried out by introducing several observation criteria, namely, water access, soil color, and soil texture. The addition of these factors has improved the initial accuracy of model to an R2 score of 0.960. As a conclusion, the developed model can provide immediate assessment of corrosion growth experienced by underground structures.
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Soil analysis: an interpretation manual
Choice Reviews Online · 1999 · 572 citations
Predictive Model for Pitting Corrosion in Buried Oil and Gas Pipelines
J.C. Velázquez, F. Caleyo, A. Valor et al. · CORROSION · 2009 · 214 citations